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基于混合模型的空气中二氧化硫浓度检测优化 被引量:1

Optimization of Sulfur Dioxide Concentration Detection in Air Based on Mixed Model
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摘要 通过改进传统比色法,提出了检测空气中二氧化硫浓度的新方法.介绍了检测空气中二氧化硫浓度的常规方法,对比传统比色法测定浓度的优缺点,提出了以红绿蓝RGB模型与HIS模型相结合的数码成像比色法的优化方案,以此建立了二氧化硫浓度与图像色彩特征值的混合数学模型.基于模型数值分析找出了匹配性较好的RGB-H模型作为快速、准确检测二氧化硫浓度的新方法,并论证了新方法在测定空气中二氧化硫浓度上的优势. A new method for detecting sulfur dioxide concentration in air was proposed by improving traditional colorimetry.The paper expounds the conventional way to detect the concentration of sulfur dioxide in the air,and compares the advantages and disadvantages of traditional colorimetry to determine concentration.An optimum scheme of digital imaging colorimetric method combining red-green-blue RGB model with HIS model is proposed.Based on this,a mixed mathematical model of sulfur dioxide concentration and image color eigenvalues is established.Based on the numerical analysis of the model,a better matching RGB-H model was found as a new method for fast and accurate determination of sulfur dioxide concentration,and the advantages of the new method in the determination of sulfur dioxide concentration in air were demonstrated.
作者 李静 程适 LI Jing;CHENG Shi(Dept.of Basic Courses,Shaanxi Railway Institute,Weinan 714000,China;School of Computer Science,Shaanxi Normal University,Xi’an 710119,China)
出处 《淮海工学院学报(自然科学版)》 CAS 2018年第4期43-46,共4页 Journal of Huaihai Institute of Technology:Natural Sciences Edition
基金 中央高校基本科研业务费专项资金项目(GK201703062) 陕西铁路工程职业技术学院科研课题(KY2016-29)
关键词 图像比色法 RGB模型 HIS模型 非线性拟合 数据分析 image colorimetry RGB model HIS model non-linear fitting data analysis
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